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About
Develop, test, and maintain complex prioritized engineering (design/build/test) work as a member of a data analytics product pipeline architecture and infrastructure team. Investigate and analyze feasibility of data integration prototypes and program requirements. Develop specifications and plan the full range of programming actions to produce data integration components. Develop and maintain complex automated ETL/ELT pipeline architecture that cleans, transforms, and aggregates data from disparate sources using architecturally approved tools, programming languages, and services to deliver a data mesh approach. Develop and maintain complex automated ETL/ELT monitoring and alarming solutions using architecturally approved languages and services. Monitor, troubleshoot, and optimize data pipelines for quality, performance, and reliability, creating a single source of truth for business customers. Build complex unit tests to enable test‑driven development and automation, driving code reliability. Develop, maintain, test, and deploy code with architecturally approved toolsets using DevOps practices, ETL/ELT pipelines, data catalogs, and data queries. Maintain data solutions in a divest state to ensure business functionality until replaced with new technology. Balance and design data analytics product solutions based on cost and performance to meet data needs and business requirements. Guide business customers to develop, troubleshoot, and optimize complex SQL and ETL/ELT solutions for reporting, metrics, and analytics problems. Collaborate with cross‑functional teams to translate data requirements into scalable and efficient data solutions. Lead moderately complex projects or support larger initiatives as part of a team. Partner with users and stakeholders to understand data needs and business requirements. Lead the team on conceptualizing and developing new data solutions to meet business data needs. Research, perform analysis, and propose effective solutions related to system developments and enhancements. Analyze and review potential adjustments for impacts on other programs. Leverage data governance, data security, and privacy principles to support data lineage and reference data needs. Collaborate to deliver data‑driven solutions that implement best practices for data management, security, and governance. Develop complex data objects for business analytics using data modeling techniques.
Model front‑end and back‑end data sources to provide a comprehensive picture of user flows. Translate complex business needs into conceptual data models, defining entities, attributes, and relationships. Build detailed logical models based on the conceptual model, specifying data types, constraints, and keys to ensure integrity. Implement logical models into appropriate database management systems, considering features, storage optimization, and performance. Design complex data pipelines to extract, transform, and load data into the target database.
Participate in creating and maintaining documentation related to the design of applications and interfaces to enterprise and third‑party systems. Collaborate with data governance to ensure data analytics products enable data governance to publish data assets. Develop and maintain data analytic products, artifacts, and user documentation for business customers. Gather and document requirements for data publishing and data consumption via data mesh architecture. Qualifications
Bachelor’s degree, preferably in a computer‑related field or equivalent relevant experience. Five years of data integration development experience, or related experience. Strong SQL knowledge and experience working with relational databases. Excellent analytical skills to work with unstructured datasets. Excellent knowledge of applicable programming languages, such as Python. Strong knowledge of cloud services such as RDS, S3, SNS, CloudWatch, and Lambda. Strong knowledge of DBT/Informatica or other ETL/ELT tools preferred. Strong knowledge of Snowflake. Strong knowledge of data modeling. Excellent ability to build processes supporting data transformation, data structures, metadata, dependency, and workload management. Excellent knowledge of orchestration or scheduling tools. Excellent verbal and written communication skills. Strong attention to detail, organizational and multi‑tasking skills with ability to adapt to changing priorities. Ability to maintain confidentiality. Strong knowledge of DevOps and/or DataOps practices, CI/CD pipelines, and containerization technologies preferred. Strong knowledge of cloud‑based data analytics platforms and security principles. Salary Range
$92,670 – $128,045 or $102,443 – $140,845, depending on geographic location. The actual salary will depend on education, skills, experience, and business needs. EMC complies with labor law requirements. View the federal and e‑verify labor law posters. Our employment practices are in accordance with the laws that prohibit discrimination due to race, color, creed, sex, sexual orientation, gender identity, genetic information, religion, age, national origin or ancestry, physical or mental disability, medical condition, veteran status, active military status, citizenship status, marital status, or any other consideration made unlawful by federal, state, or local laws. All of our locations are tobacco free, including company vehicles.
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